Question 2- Plotly from Assignment 3
Assignment 3- Question 2
dat_class= read.table("https://raw.githubusercontent.com/bcaffo/ds4bme/master/data/classInterests.txt", header=TRUE)
library(ggplot2)
library(plotly)
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## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
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## last_plot
## The following object is masked from 'package:stats':
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## filter
## The following object is masked from 'package:graphics':
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## layout
class_plot <- ggplot(dat_class,aes(x=Year,fill= Program))
class_plot = class_plot + geom_bar()
ggplotly(class_plot)
Assignment 3- Question 3
library(ggmosaic)
dat_class= read.table("https://raw.githubusercontent.com/bcaffo/ds4bme/master/data/classInterests.txt", header=TRUE)
mosaic_class <- ggplot(data=dat_class) +
geom_mosaic(aes(x=product(Year), fill = Program))
ggplotly(mosaic_class)
Assignment 3- Question 5
dat_health= read.csv("https://raw.githubusercontent.com/jhu-advdatasci/2018/master/data/KFF/healthcare-spending.csv", skip=2)
dat_health_states <- dat_health[-c(1,53:61),]
library(reshape)
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## Attaching package: 'reshape'
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## rename
health_states_melt <- melt(dat_health_states, id.vars = "Location")
health_plot <- ggplot(health_states_melt,aes(x=variable, y=value, group= Location, color=Location))
health_plot = health_plot + geom_line()
health_plot = health_plot + theme(axis.text.x = element_text(angle = 90))
ggplotly(health_plot)
Assignment 3- Question 6
avg<- rowMeans(dat_health_states[,-1])
health_states_avg <- data.frame(Location=dat_health_states[,1], Spending= avg)
health_barplot <- ggplot(health_states_avg, aes(x=Location, y=Spending))
health_barplot <- health_barplot + geom_col()
health_barplot = health_barplot + theme(axis.text.x = element_text(angle = 90))
ggplotly(health_barplot)